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Atmosphere, Volume 9, Issue 2 (February 2018)

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Cover Story (view full-size image) In coastal California, the chemical mixing state and ability of aerosol particles to nucleate cloud [...] Read more.
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Open AccessArticle Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China
Atmosphere 2018, 9(2), 78; https://doi.org/10.3390/atmos9020078
Received: 18 November 2017 / Revised: 17 February 2018 / Accepted: 19 February 2018 / Published: 22 February 2018
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Abstract
Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it
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Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100~670 m, but exponentially decreased between the heights of 670~1800 m. Both the correlation and the variation tendency of simulated PBLH from the Weather Research and Forecasting (WRF) model & Shin-Hong (SHIN)/California Meteorological (CALMET) model (WRF_SHIN/CALMET) were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated the Planetary Boundary Layer Height (PBLH) could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle Innovative Hybrid Modeling of Wind Speed Prediction Involving Time-Series Models and Artificial Neural Networks
Atmosphere 2018, 9(2), 77; https://doi.org/10.3390/atmos9020077
Received: 2 January 2018 / Revised: 3 February 2018 / Accepted: 6 February 2018 / Published: 21 February 2018
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Abstract
This work proposes hybrid models combining time-series models (using linear functions) and artificial intelligence (using a nonlinear function) that can be used to provide monthly mean wind speed predictions for the Brazilian northeast region. These might be useful for wind power generation; for
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This work proposes hybrid models combining time-series models (using linear functions) and artificial intelligence (using a nonlinear function) that can be used to provide monthly mean wind speed predictions for the Brazilian northeast region. These might be useful for wind power generation; for example, they could acquire important information on how the local wind potential can be usable for a possible wind power plant through understanding future wind speed values. To create the proposed hybrid models, it was necessary to set the wind speed variable as a dependent variable of exogenous variables (i.e., pressure, temperature, and precipitation). Thus, it was possible to consider the meteorological characteristics of the study regions. It is possible to verify the hybrid models’ efficiency in providing perfect adjustments to the observed data. This statement is based on the low values found in the error statistical analysis, i.e., an error of approximately 5.0% and a Nash–Sutcliffe coefficient near to 0.96. These results were certainly important in predicting the wind speed time-series, which was similar to the observed wind speed time-series profile. Great similarities of maximums and minimums between the series were evident and showed the capacity of the models to represent the seasonality characteristics. Full article
(This article belongs to the Section Climatology and Meteorology)
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Open AccessReview Recent Advances in Atmospheric Chemistry of Mercury
Atmosphere 2018, 9(2), 76; https://doi.org/10.3390/atmos9020076
Received: 20 January 2018 / Revised: 13 February 2018 / Accepted: 15 February 2018 / Published: 21 February 2018
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Abstract
Mercury is one of the most toxic metals and has global importance due to the biomagnification and bioaccumulation of organomercury via the aquatic food web. The physical and chemical transformations of various mercury species in the atmosphere strongly influence their composition, phase, transport
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Mercury is one of the most toxic metals and has global importance due to the biomagnification and bioaccumulation of organomercury via the aquatic food web. The physical and chemical transformations of various mercury species in the atmosphere strongly influence their composition, phase, transport characteristics and deposition rate to the ground. Modeling efforts to evaluate the mercury cycling in the environment require an accurate understanding of atmospheric mercury chemistry. We focus this article on recent studies (since 2015) on improving our understanding of the atmospheric chemistry of mercury. We discuss recent advances in (i) determining the dominant atmospheric oxidant of elemental mercury (Hg0); (ii) understanding the oxidation reactions of Hg0 by halogen atoms and by nitrate radical (NO3); (iii) the aqueous reduction of oxidized mercury compounds (HgII); and (iv) the heterogeneous reactions of Hg on atmospherically-relevant surfaces. The need for future research to improve understanding of the fate and transformation of mercury in the atmosphere is also discussed. Full article
(This article belongs to the Special Issue Atmospheric Metal Pollution)
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Open AccessArticle Indoor Air Quality and Thermal Conditions in a Primary School with a Green Roof System
Atmosphere 2018, 9(2), 75; https://doi.org/10.3390/atmos9020075
Received: 30 November 2017 / Revised: 16 February 2018 / Accepted: 17 February 2018 / Published: 20 February 2018
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Abstract
This paper presents experimental results from a typical school building in Athens, equipped partly with a green roof system (GRS). Environmental monitoring took place in six classrooms located both under the concrete roof and the GRS sectors as well as in the immediate
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This paper presents experimental results from a typical school building in Athens, equipped partly with a green roof system (GRS). Environmental monitoring took place in six classrooms located both under the concrete roof and the GRS sectors as well as in the immediate external environment during the warm and cold periods of a school year. Daily measurements of pollutants CO2, TVOCs (Total Volatile Organic Compound), PM1, PM2.5, and PM10 were performed in selected classes. Moreover, indoor ambient temperature (T) and relative humidity (RH) measurements were implemented in order to estimate the absolute humidity (AH) and assess the indoor environmental conditions. The results highlight that during summer, the GRS reduces temperature in a classroom on the top floor by about 2.8 °C, in comparison with the respective classroom under the concrete roof and that AH remained relatively stable for both classrooms. Amid winter, a reverse behavior occurs only for temperature. Moreover, air exchange rates (AER) were calculated by using the CO2 decay method for all of the classrooms. The results demonstrated insufficient ventilation for all experimental sights. Finally, concentrations of PM1, PM2.5 and PM10, were found to be relatively decreased, with average values of 0.79, 3.39, and 27.80 μg m−3. Levels of CO2 and TVOCs were elevated during class hours ranging from 469 to 779 ppm and from 6.63 ppm to 13.33 ppm, respectively, but generally within the respective limits of exposure. The examination of the indoor/outdoor (I/O) ratio of air pollutants, demonstrated that the outdoor meteorology affects only PM1 and PM2.5, as PM10 and TVOCs are strongly affected by internal sources and the activities of pupils. Full article
(This article belongs to the Special Issue Advances in Atmospheric Physics: Selected Papers from CEST2017)
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Open AccessArticle Spatiotemporal Characteristics of Air Pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) in the Inland Basin City of Chengdu, Southwest China
Atmosphere 2018, 9(2), 74; https://doi.org/10.3390/atmos9020074
Received: 4 October 2017 / Revised: 13 February 2018 / Accepted: 13 February 2018 / Published: 16 February 2018
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Abstract
Most cities in China are experiencing severe air pollution due to rapid economic development and accelerated urbanization. Long-term air pollution data with high temporal and spatial resolutions are needed to support research into physical and chemical processes that affect air quality, and the
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Most cities in China are experiencing severe air pollution due to rapid economic development and accelerated urbanization. Long-term air pollution data with high temporal and spatial resolutions are needed to support research into physical and chemical processes that affect air quality, and the corresponding health risks. For the first time, data on PM10, PM2.5, SO2, NO2, O3 and CO concentrations in 23 ambient air quality automatic monitoring stations and routine meteorological were collected between January 2014 and December 2016 to determine the spatial and temporal variation in these pollutants and influencing factors in Chengdu. The annual mean concentrations of PM2.5 and PM10 exceeded the standard of Chinese Ambient Air Quality and World Health Organization guidelines standards at all of the stations. The concentrations of PM10, PM2.5, SO2 and CO decreased from 2014 to 2016, and the NO2 level was stable, whereas the O3 level increased markedly during this period. The air pollution characteristics in Chengdu showed simultaneously high PM concentrations and O3. High PM concentrations were mainly observed in the middle region of Chengdu and may have been due to the joint effects of industrial and vehicle emissions. Ozone pollution was mainly due to vehicle emissions in the downtown area, and industry had a more important effect on O3 in the northern area with fewer vehicles. The concentrations of PM10, PM2.5, NO2 and CO were highest in winter and lowest in summer; the highest SO2 concentration was also observed in winter and was lowest in autumn, whereas the O3 concentration peaked in summer. Haze pollution can easily form under the weather conditions of static wind, low temperature and relative humidity, and high surface pressure inside Chengdu. In contrast, severe ozone pollution is often associated with high temperature. Full article
(This article belongs to the Section Air Quality)
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Open AccessArticle Comparative Evaluation of the Third-Generation Reanalysis Data for Wind Resource Assessment of the Southwestern Offshore in South Korea
Atmosphere 2018, 9(2), 73; https://doi.org/10.3390/atmos9020073
Received: 31 December 2017 / Revised: 12 February 2018 / Accepted: 14 February 2018 / Published: 16 February 2018
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Abstract
This study evaluated the applicability of long-term datasets among third-generation reanalysis data CFSR, ERA-Interim, MERRA, and MERRA-2 to determine which dataset is more suitable when performing wind resource assessment for the ‘Southwest 2.5 GW Offshore Wind Power Project’, which is currently underway strategically
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This study evaluated the applicability of long-term datasets among third-generation reanalysis data CFSR, ERA-Interim, MERRA, and MERRA-2 to determine which dataset is more suitable when performing wind resource assessment for the ‘Southwest 2.5 GW Offshore Wind Power Project’, which is currently underway strategically in South Korea. The evaluation was performed by comparing the reanalyses with offshore, onshore, and island meteorological tower measurements obtained in and around the southwest offshore. In the pre-processing of the measurement data, the shading sectors due to a meteorological tower were excluded from all observation data, and the measurement heights at the offshore meteorological towers were corrected considering the sea level change caused by tidal difference. To reflect the orographic forcing by terrain features, the reanalysis data were transformed by using WindSim, a flow model based on computational fluid dynamics and statistical-dynamic downscaling. The comparison of the reanalyses with the measurement data showed the fitness in the following order in terms of coefficient of determination: MERRA-2 > CFSR = MERRA > ERA-Interim. Since the measurement data at the onshore meteorological towers strongly revealed a local wind system such as sea-land breeze, it is judged to be inappropriate for use as supplementary data for offshore wind resource assessment. Full article
(This article belongs to the Special Issue Energy Meteorology)
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Open AccessArticle 2004–2016 Wintertime Atmospheric Blocking Events over Western Siberia and Their Effect on Surface Temperature Anomalies
Atmosphere 2018, 9(2), 72; https://doi.org/10.3390/atmos9020072
Received: 23 December 2017 / Revised: 12 February 2018 / Accepted: 13 February 2018 / Published: 16 February 2018
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Abstract
Western Siberia is a large area in Northern Eurasia, which lies between the Urals and the Yenisei River. The atmospheric blocking events are not a frequent phenomenon in this region. Nevertheless, they noticeably affect the weather and living conditions of people there. We
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Western Siberia is a large area in Northern Eurasia, which lies between the Urals and the Yenisei River. The atmospheric blocking events are not a frequent phenomenon in this region. Nevertheless, they noticeably affect the weather and living conditions of people there. We have investigated 14 winter blocking events, identified over Western Siberia, over 2004–2016, and have studied their effect on the surface temperature in this region. We have compared each of the 14 blocking events to the corresponding surface temperature anomalies in the north and in the south of Western Siberia. As a result, the temperature anomalies were separated into two groups: (1) dipole, with a positive surface temperature anomaly (or close to the norm) in the north, and with a negative anomaly (or close to the norm) in the south, and (2) non-dipole. Ten events were attributed to Group 1, four events were referred to Group 2. Analyzing the potential temperature on the dynamic tropopause (advection characteristic) showed that the Group 1 events feature strong advection over the investigated territory. In the non-dipole situations from Group 2 Western Siberia are away from strong blocking events. Full article
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Open AccessArticle Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method
Atmosphere 2018, 9(2), 71; https://doi.org/10.3390/atmos9020071
Received: 18 January 2018 / Revised: 9 February 2018 / Accepted: 10 February 2018 / Published: 15 February 2018
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Abstract
Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to
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Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to quantitatively estimate the uncertainty of areal rainfall estimates and its effects on hydrological simulations. The observed rainfall records are first analyzed using clustering and correlation methods and possible average basin rainfall amounts are calculated with a bootstrap method using various combinations of rainfall station subsets. Then, the uncertainty of simulated runoff, which is propagated through a hydrological model from the spatial uncertainty of rainfall estimates, is analyzed with the bootstrapped rainfall inputs. By comparing the uncertainties of rainfall and runoff, the responses of the hydrological simulation to the rainfall spatial uncertainty are discussed. Analyses are primarily performed for three rainfall events in the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River; moreover, one rainfall event in the Longxi River basin is selected for the analysis of the areal representation of rainfall stations. Using the Digital Yellow River Integrated Model, the results show that the uncertainty of rainfall estimates derived from rainfall station network has a direct influence on model simulation, which can be conducive to better understand of rainfall spatial characteristic. The proposed method can be a guide to quantify an approximate range of simulated error caused by the spatial uncertainty of rainfall input and the quantified relationship between rainfall input and simulation performance can provide useful information about rainfall station network management in river basins. Full article
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Open AccessArticle Evaluation of Analysis by Cross-Validation, Part II: Diagnostic and Optimization of Analysis Error Covariance
Atmosphere 2018, 9(2), 70; https://doi.org/10.3390/atmos9020070
Received: 7 November 2017 / Revised: 19 January 2018 / Accepted: 13 February 2018 / Published: 15 February 2018
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Abstract
We present a general theory of estimation of analysis error covariances based on cross-validation as well as a geometric interpretation of the method. In particular, we use the variance of passive observation-minus-analysis residuals and show that the true analysis error variance can be
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We present a general theory of estimation of analysis error covariances based on cross-validation as well as a geometric interpretation of the method. In particular, we use the variance of passive observation-minus-analysis residuals and show that the true analysis error variance can be estimated, without relying on the optimality assumption. This approach is used to obtain near optimal analyses that are then used to evaluate the air quality analysis error using several different methods at active and passive observation sites. We compare the estimates according to the method of Hollingsworth-Lönnberg, Desroziers et al., a new diagnostic we developed, and the perceived analysis error computed from the analysis scheme, to conclude that, as long as the analysis is near optimal, all estimates agree within a certain error margin. Full article
(This article belongs to the Special Issue Air Quality Monitoring and Forecasting) Printed Edition available
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Open AccessArticle The 30–50-Day Intraseasonal Oscillation of SST and Precipitation in the South Tropical Indian Ocean
Atmosphere 2018, 9(2), 69; https://doi.org/10.3390/atmos9020069
Received: 15 November 2017 / Revised: 6 February 2018 / Accepted: 9 February 2018 / Published: 15 February 2018
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Abstract
The Sea Surface Temperature (SST) in the South Tropical Indian Ocean (STIO) displays significant intraseasonal oscillation (ISO) in two regions. A striking 30–50-day ISO found over the east of thermocline ridge (Region A, 80–90° E, 6–12° S), as identified by the Empirical Mode
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The Sea Surface Temperature (SST) in the South Tropical Indian Ocean (STIO) displays significant intraseasonal oscillation (ISO) in two regions. A striking 30–50-day ISO found over the east of thermocline ridge (Region A, 80–90° E, 6–12° S), as identified by the Empirical Mode Decomposition (EMD) method, is distinguished from the SST signature over the thermocline ridge (Region B, 52.5–65° E, 6–13° S). The 30–50-day ISO of SST in the Region A is active in March–May (MAM) and suppressed in September–November (SON). Meanwhile, a 30–50-day ISO of precipitation correlates with the SST over the Region A. SST leads precipitation by 10 days, implying a pronounced ocean–atmosphere interaction at the intraseasonal timescale, especially the oceanic feedback to the atmosphere during Madden–Julian Oscillation (MJO) events. Analysis on mechanism of the ISO manifests heat fluxes are critical to the development of the intraseasonal SST variability. The local thermocline in Region A, as the shallowest in MAM and the thickest in SON, is likely to modulate the strength of ISO and contribute to its sustainability. It suggests that thermocline plays a more important role in Region A than in Region B, leading to the difference between the two regions. Full article
(This article belongs to the Special Issue Madden-Julian Oscillation)
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Open AccessArticle Observing Actual Evapotranspiration from Flux Tower Eddy Covariance Measurements within a Hilly Watershed: Case Study of the Kamech Site, Cap Bon Peninsula, Tunisia
Atmosphere 2018, 9(2), 68; https://doi.org/10.3390/atmos9020068
Received: 22 December 2017 / Revised: 25 January 2018 / Accepted: 31 January 2018 / Published: 15 February 2018
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Abstract
There is a strong need for long term observations of land surface fluxes such as actual evapotranspiration (ETa). Eddy covariance (EC) method is widely used to provide ETa measurements, and several gap-filling methods have been proposed to complete inherent missing data. However, implementing
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There is a strong need for long term observations of land surface fluxes such as actual evapotranspiration (ETa). Eddy covariance (EC) method is widely used to provide ETa measurements, and several gap-filling methods have been proposed to complete inherent missing data. However, implementing gap-filling methods is questionable for EC time series collected within hilly agricultural areas at the watershed extent. Indeed, changes in wind direction induce changes in airflow inclination and footprint, and therefore possibly induce changes in the relationships on which rely gap-filling methods. This study aimed to obtain continuous ETa time series by adapting gap-filling methods to the particular conditions abovementioned. The experiment took place within an agricultural watershed in north-eastern Tunisia. A 9.6-m-high EC flux tower has been operating close to the watershed center since 2010. The sensible and latent heat fluxes data collected from 2010 to 2013 were quality controlled, and the REddyProc software was used to fill gaps at the hourly timescale. Adapting REddyProc method consisted of splitting the dataset according to wind direction, which improved the flux data at the hourly timescale, but not at the daily and monthly timescales. Finally, complete time series permitted to analyze seasonal and inter-annual variability of ETa. Full article
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Open AccessArticle Activity Characteristics of the East Asian Trough in CMIP5 Models
Atmosphere 2018, 9(2), 67; https://doi.org/10.3390/atmos9020067
Received: 19 December 2017 / Revised: 8 February 2018 / Accepted: 12 February 2018 / Published: 14 February 2018
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Abstract
In this paper, the performances of 12 CMIP5 (Coupled Model Intercomparison Project phase 5) models for simulating the climatology and interannual variability of the East Asian trough (EAT) are assessed using the National Centers for Environmental Prediction (NCEP) reanalysis data and the outputs
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In this paper, the performances of 12 CMIP5 (Coupled Model Intercomparison Project phase 5) models for simulating the climatology and interannual variability of the East Asian trough (EAT) are assessed using the National Centers for Environmental Prediction (NCEP) reanalysis data and the outputs of the CMIP5 models. The multimodel ensemble (MME) successfully reproduces the spatial pattern and spatial variations in the climatology and interannual variability of the EAT but the intensity and interannual variability of EAT are weaker than in the observations. The biases in intensity (interannual variability) are larger over the southern (northern) part of the EAT than over the northern (southern) part. The intermodel spreads are small for the EAT intensity but are large for its location in terms of both latitude and longitude. The simulated EAT in the MME is about 3° E and 1.5° S of that observed. All 12 CMIP5 models reproduce the first empirical orthogonal function (EOF) mode of EAT activity; however, its intensity and location are only successfully captured in half of the models and its linear weakening trend is simulated in ten models. The second EOF mode of EAT activity and its linear strengthening trend are successfully reproduced in eight models. Full article
(This article belongs to the Special Issue Monsoons)
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Open AccessArticle Effect of Teleconnection Patterns on Changes in Water Temperature in Polish Lakes
Atmosphere 2018, 9(2), 66; https://doi.org/10.3390/atmos9020066
Received: 7 November 2017 / Revised: 12 February 2018 / Accepted: 12 February 2018 / Published: 14 February 2018
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Abstract
The objective of the paper was the determination of the effect of teleconnection patterns (North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East Atlantic pattern (EA), East Atlantic/Western Russia (EAWR), and Scandinavian pattern (SCAND)) on changes in air and water temperature in Polish lakes.
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The objective of the paper was the determination of the effect of teleconnection patterns (North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East Atlantic pattern (EA), East Atlantic/Western Russia (EAWR), and Scandinavian pattern (SCAND)) on changes in air and water temperature in Polish lakes. Correlations of circulation indices with air and lake water temperature were analysed in the monthly cycle. Deviations of values of such components in different phases of the analysed atmospheric circulations types from mean average from the years 1971 to 2015 were also determined. The research showed a variable effect of the atmospheric circulations types. The strongest effect on water temperature was observed in winter, when AO and NAO circulation showed particularly evident influence. Deviations of water temperature from mean values from the analysed multi-annual period generally oscillated around 1.0 °C, reaching a maximum value of 1.4 °C. The presented research shows the complexity of processes determining changes in lake water temperature, the course of which depends on many factors with both regional (e.g., ice cover on lakes) and local range (conditions of water exchange, human pressure). Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land - Atmosphere Interactions)
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Open AccessArticle Ventilation and Air Quality in City Blocks Using Large-Eddy Simulation—Urban Planning Perspective
Atmosphere 2018, 9(2), 65; https://doi.org/10.3390/atmos9020065
Received: 2 January 2018 / Revised: 9 February 2018 / Accepted: 11 February 2018 / Published: 13 February 2018
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Abstract
Buildings and vegetation alter the wind and pollutant transport in urban environments. This comparative study investigates the role of orientation and shape of perimeter blocks on the dispersion and ventilation of traffic-related air pollutants, and the street-level concentrations along a planned city boulevard.
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Buildings and vegetation alter the wind and pollutant transport in urban environments. This comparative study investigates the role of orientation and shape of perimeter blocks on the dispersion and ventilation of traffic-related air pollutants, and the street-level concentrations along a planned city boulevard. A large-eddy simulation (LES) model PALM is employed over a highly detailed representation of the urban domain including street trees and forested areas. Air pollutants are represented by massless and passive particles (non-reactive gases), which are released with traffic-related emission rates. High-resolution simulations for four different city-block-structures are conducted over a 8.2 km 2 domain under two contrasting inflow conditions with neutral and stable atmospheric stratification corresponding the general and wintry meteorological conditions. Variation in building height together with multiple cross streets along the boulevard improves ventilation, resulting in 7–9% lower mean concentrations at pedestrian level. The impact of smaller scale variability in building shape was negligible. Street trees further complicate the flow and dispersion. Notwithstanding the surface roughness, atmospheric stability controls the concentration levels with higher values under stably stratified inflow. Little traffic emissions are transported to courtyards. The results provide urban planners direct information to reduce air pollution by proper structural layout of perimeter blocks. Full article
(This article belongs to the Special Issue Recent Advances in Urban Ventilation Assessment and Flow Modelling)
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Open AccessArticle Electrostatic Dust Cloth: A Passive Screening Method to Assess Occupational Exposure to Organic Dust in Bakeries
Atmosphere 2018, 9(2), 64; https://doi.org/10.3390/atmos9020064
Received: 26 September 2017 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 12 February 2018
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Abstract
Organic dust is widespread in the environment including occupational settings, such as bakeries. Recently, a new collection device—the electrostatic dust cloth (EDC)—has been described for the assessment of occupational exposures. The aim of this study was to investigate the suitability of EDC for
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Organic dust is widespread in the environment including occupational settings, such as bakeries. Recently, a new collection device—the electrostatic dust cloth (EDC)—has been described for the assessment of occupational exposures. The aim of this study was to investigate the suitability of EDC for identifying the distribution patterns and exposure concentrations of particulate matter and microbial contaminants such as fungi and bacteria in bakeries. Twelve bakeries were selected, and dust was allowed to settle for 13 to 16 days on EDCs (a total of 33 samples). Particle counts and size distribution (0.3 µm, 0.5 µm, 1 µm, 2.5 µm, 5 µm and 10 µm) were measured with direct-reading equipment. Higher EDC mass was significantly correlated (p values < 0.05) with higher fungal load on dichloran glycerol (DG18) and with particle size distribution in the 0.3 µm, 0.5 µm, 1.0 µm and 10.0 µm range. Fungal levels on malt extract agar (MEA) ranged from 0 to 2886 CFU/m2 EDC in the warehouse setting, 0 to 500 CFU/m2 EDC in the production setting, and 0 to 3135 CFU/m2 EDC in the store. Penicillium sp. (42.56%) was the most frequent fungi. Total bacterial load ranged from 0 to 18,859 CFU/m2 EDC in the warehouse, 0 to 71,656 CFU/m2 EDC in production, and 0 to 21,746 CFU/m2 EDC in the store. EDC assessment provided a longer-term integrated sample of organic dust, useful for identifying critical worksites in which particulate matter and bio-burden exposures are elevated. These findings suggest that EDC can be applied as a screening method for particulate matter-exposure assessment and as a complementary method to quantify exposures in occupational environments. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
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